title: Healthcare information technology's relativity problems: a typology of how patients' physical reality, clinicians' mental models, and healthcare information technology differ.
abstract: OBJECTIVE
  To model inconsistencies or distortions among three realities: patients' physical reality; clinicians' mental models of patients' conditions, laboratories, etc; representation of that reality in electronic health records (EHR). To serve as a potential tool for quality improvement of EHRs.
  
  
  METHODS
  Using observations, literature, information technology (IT) logs, vendor and US Food and Drug Administration reports, we constructed scenarios/models of how patients' realities, clinicians' mental models, and EHRs can misalign to produce distortions in comprehension and treatment. We then categorized them according to an emergent typology derived from the cases themselves and refined the categories based on insights gained from the literature of interactive sociotechnical systems analysis, decision support science, and human computer interaction. Typical of grounded theory methods, the categories underwent repeated modifications.
  
  
  RESULTS
  We constructed 45 scenarios of misalignment between patients' physical realities, clinicians' mental models, and EHRs. We then identified five general types of misrepresentation in these cases: IT data too narrowly focused; IT data too broadly focused; EHRs miss critical reality; data multiplicities-perhaps contradictory or confusing; distortions from data reflected back and forth across users, sensors, and others. The 45 scenarios are presented, organized by the five types.
  
  
  CONCLUSIONS
  With humans, there is a physical reality and actors' mental models of that reality. In healthcare, there is another player: the EHR/healthcare IT, which implicitly and explicitly reflects many mental models, facets of reality, and measures thereof that vary in reliability and consistency. EHRs are both microcosms and shapers of medical care. Our typology and scenarios are intended to be useful to healthcare IT designers and implementers in improving EHR systems and reducing the unintended negative consequences of their use.
authors.affiliation: Department of Computer Science, Dartmouth College, Hanover, New Hampshire, USA.
authors.forename: Sean W
authors.initials: SW
authors.lastname: Smith
authors.forename: Ross
authors.initials: R
authors.lastname: Koppel
mesh_terms: D057286:Electronic Health Records; D006282:Health Personnel / Q000523:psychology*; D006801:Humans; D008490:Medical Informatics; D008960:Models, Psychological; D008962:Models, Theoretical; D005791:Patient Care; D010361:Patients / Q000523:psychology*
keywords: Continuous quality improvement; Modeling Interactions; Quality improvement; Typology Development